========================================================================= 
Log Path: ./log/logsupplementary.log 
Program Path: /Users/yorke/Dropbox/dissertation/3_Empirics/2_Code/vote_mobilization_code/replication/03_rep_supplementary.R 
Working Directory: /Users/yorke/Dropbox/dissertation/3_Empirics/2_Code/vote_mobilization_code/replication 
User Name: yorke 
R Version: 4.3.1 (2023-06-16) 
Machine: AS23C1Q05N arm64 
Operating System: Darwin 21.6.0 Darwin Kernel Version 21.6.0: Mon Aug 22 20:20:05 PDT 2022; root:xnu-8020.140.49~2/RELEASE_ARM64_T8101 
Base Packages: stats graphics grDevices utils datasets methods base 
Other Packages: tidylog_1.1.0 MASS_7.3-60 vdemdata_13.0 xtable_1.8-4 logr_1.3.8 common_1.1.3 sandwich_3.0-2 stargazer_5.2.3 lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4 purrr_1.0.2 readr_2.1.5 tidyr_1.3.1 tibble_3.2.1 ggplot2_3.5.1 tidyverse_2.0.0 
Log Start Time: 2024-06-03 17:27:27.439536 
========================================================================= 

> #### Replication Code for:
> #### Constituency Service and Electoral Accountability in Autocratic Legislatures
> #### Author: Erin York
> #### Created: 5/30/2024
> 
> # this code replicates most data-generated figures and tables in the supplementary appendix
> # for figure A4 and Table A15, see alternate file XX
> 
> rm(list = ls())
> 
> ## Load Packages
> library(tidyverse)
> library(stargazer)
> library(xtable)
> library(vdemdata)
> # if you do not have the vdemdata package installed, you can uncomment the following lines of code:
> #install.packages("devtools")
> #devtools::install_github("vdeminstitute/vdemdata")
> library(MASS)
> 
> library(logr)
> 
> options("logr.autolog" = TRUE)
> 
> # Open the log
> lf <- log_open(file.path("logsupplementary.log"))
> 
> # Send message to log
> log_code()
> 
> 
> 
> # load data ---------------------------------------------------------------
> 
> 
> # load cross-national dataset
> country_panel<- read_csv("df_country_panel.csv")
> # load subnational data
> # politician level
> mpdat<- read_csv("df_mplevel.csv")
> # query level
> querydat<- read_csv("df_querylevel.csv")
> # party-circonscription level
> partycirc<- read_csv("df_partylevel.csv")
> # party-municipality level
> munidat<- read_csv("df_munilevel.csv")
> 
> 
> 
> 
> ## helper functions ------------------------------------------------------------
> 
> # for cluster bootstrapping
> block_bs <- function(clust, dat, model){
>   nclust <- length(unique(clust))
>   levels <- unique(clust)
>   samp <- as.vector(sample(levels, size = nclust, replace = T))
>   orig <- clust
>   dat2 <- plyr::ldply(lapply(samp, FUN = function(x){dat[orig == x,]}), data.frame)
>   a <- lm(as.formula(model), data = dat2)
>   return(c(coef(a)))
> }
> 
> # for cluster bootstrapping - negative binomial
> block_bs_nb <- function(){
>   nclust <- length(unique(mpdat$partyid))
>   levels <- unique(mpdat$partyid)
>   samp <- as.vector(sample(levels, size = nclust, replace = T))
>   orig <- mpdat$partyid
>   dat <- plyr::ldply(lapply(samp, FUN = function(x){mpdat[orig == x,]}), data.frame)
>   a <- glm.nb(nwrit ~ royalist, data = dat, init.theta = 0.4284)
>   b <- glm.nb(nwrit ~ royalist + leader + natlist +
>                 former + actif, data = dat, init.theta = 0.4509)
>   c <- glm.nb(nwrit ~ royalist + gov_full + leader + female + youth +
>                 former + actif, data = dat, init.theta = 0.4712)
>   return(c(coef(a)[1:2], coef(b)[1:6], coef(c)[1:8]))
> }
> 
> # figure A1 ---------------------------------------------------------------
> 
> 
> ## Figure A1
> fa1<- country_panel %>%
>   filter(gov1seat > 0, execme != "-999", totalseats > 0) %>% 
>   mutate(seatsharegov = gov1seat/totalseats,
>          seatsharenongov = 1-seatsharegov) %>%
>   group_by(year) %>%
>   summarise(mu = mean(seatsharegov), cilo = quantile(seatsharegov, .05), cihi = quantile(seatsharegov, .95),
>             n = n()) %>%
>   ggplot(aes(x = year, y = mu)) + 
>   geom_pointrange(aes(ymin = cilo, ymax = cihi), color = "gray", size = .3) + geom_point() +
>   theme_bw() + ylim(c(0, 1)) + xlab("") + ylab("Prop. seats held by largest party")
> ggsave(fa1, filename = "FigureA1.pdf",
>              width = 8, height = 5)
> 
> 
> # figure A2 ---------------------------------------------------------------
> 
> 
> ## Figure A2
> fa2<- country_panel %>%
>   filter(execme == gov1me, execme != "-999", totalseats > 0) %>% 
>   mutate(seatsharegov = gov1seat/totalseats,
>          seatsharenongov = 1-seatsharegov) %>%
>   group_by(year, v2x_regime) %>%
>   summarise(mu = mean(seatsharegov), cilo = quantile(seatsharegov, .05), cihi = quantile(seatsharegov, .95),
>             n = n()) %>%
>   ggplot(aes(x = year, y = mu, color = as.factor(v2x_regime), shape = as.factor(v2x_regime))) + 
>   geom_point() +
>   geom_line() +
>   scale_color_brewer(palette = "Paired", name = "Regime Type", labels = c("Closed autocracy", "Electoral Autocracy")) +
>   scale_shape(name = "Regime Type",  labels = c("Closed autocracy", "Electoral Autocracy")) +
>   theme_bw() + ylim(c(0, 1.05)) + xlab("") + ylab("Prop. seats held by ruling party")+
>   theme(legend.position = "bottom") +
>   geom_smooth()
> ggsave(fa2, filename = "FigureA2.pdf",
>                       width = 8, height = 5)
> 
> # figure A3 ---------------------------------------------------------------
> 
> 
> ## Figure A3
> fa3<- country_panel %>%
>   filter(execme == gov1me, execme != "-999", totalseats > 0, e_region_world_2 %in% c(1, 2, 3, 4, 7)) %>% 
>   mutate(seatsharegov = gov1seat/totalseats,
>          seatsharenongov = 1-seatsharegov) %>%
>   group_by(year, e_region_world_2) %>%
>   summarise(mu = mean(seatsharegov), cilo = quantile(seatsharegov, .05), cihi = quantile(seatsharegov, .95),
>             n = n()) %>%
>   filter(n > 2)%>%
>   ggplot(aes(x = year, y = mu, color = as.factor(e_region_world_2), shape = as.factor(e_region_world_2))) + 
>   geom_line() + geom_point() +
>   scale_color_manual(values = c("#D7191C", "#FC8D59", "#FEE08B", "#ABDDA4", "#2B83BA", "#99D594"), 
>                      name = "Region", labels = c("Eastern Europe and post-Soviet Union", 
>                                                  "Latin America",
>                                                  "North Africa and Middle East",
>                                                  "Sub-Saharan Africa", "Southeast Asia")) +
>   scale_shape(name = "Region", labels = c("Eastern Europe and post-Soviet Union", "Latin America",
>                                           "North Africa and Middle East",
>                                           "Sub-Saharan Africa", "Southeast Asia")) +
>   theme_bw() + ylim(c(0, 1)) + xlab("") + ylab("Prop. seats held by ruling party")+
>   theme(legend.position = "bottom") +
>   guides(col = guide_legend(nrow = 2))
> ggsave(fa3, filename = "FigureA3.pdf",
>        width = 8, height = 5)
> 
> 
> # figure A4 ---------------------------------------------------------------
> 
> ## see 04_rep_external.R
> 
> 
> # figure A5 ---------------------------------------------------------------
> 
> 
> fa5<- partycirc %>%
>   filter(opposition == 1) %>%
>   group_by(circid) %>%
>   summarise(oppvote2011 = sum(voteshare2011),
>             oppvote2016 = sum(voteshare2016),
>             delta = oppvote2016-oppvote2011) %>%
>   ggplot(aes(x = delta)) +
>   geom_histogram() + theme_bw() + 
>   xlab("District Change in Voteshare 2011-2016 - All Nonroyalist Parties") + 
>   ylab("")
> ggsave(fa5, filename = "FigureA5.pdf",
>        width = 8, height = 5)
> 
> 
> # figure A6 ---------------------------------------------------------------
> 
> fa6<- querydat %>%
>   mutate(Nation =natdum,
>          Region = regdum,
>          Commune = commdum,
>          Georeference = anyplace,
>          Casework = casework,
>          Complaint = complaint,
>          Province = ifelse(provdum + prefdum > 0, 1, 0),
>          Royalist = as.numeric(partyid %in% c("RNI", "UC", "PAM", "MP"))) %>%
>   dplyr::select(Nation:Royalist) %>%
>   group_by(Royalist) %>%
>   dplyr::summarise_each(funs(mean)) %>%
>   gather(attribute, mn, Nation:Province) %>%
>   mutate(attribute = fct_reorder(attribute, mn),
>          rounded = round(mn, digits = 2),
>          Royalist = plyr::mapvalues(Royalist, from = c(0, 1), to = c("No", "Yes"))) %>%
>   ggplot(aes(x = attribute, y = mn, fill = Royalist)) +
>   geom_bar(stat = "identity", position = "dodge") +
>   geom_text(aes(label = rounded, hjust = -.5),position = position_dodge(width=1)) +
>   ylim(c(0, 1)) +
>   theme_bw() +
>   coord_flip() +
>   ylab("Proportion of queries with specified content reference") +
>   xlab("") +
>   scale_fill_manual(values = c("#5cb0e0", "#CA0020")) +
>   theme(legend.position = "bottom")
> ggsave(fa6, filename = "FigureA6.pdf",
>        width = 8, height = 5)
> 
> # table A1 ----------------------------------------------------------------
> 
> # load vdem package
> vdem<- vdem
> # generate summary statistics
> # note table was formatted by hand
> ta1<- vdem %>%
>   filter(year %in% c(1995, 2005, 2015) & v2x_regime <= 1) %>% group_by(year) %>% 
>   summarise(exec_queries = mean(v2lgqstexp_ord, na.rm = T),
>             bill_prop = mean(v2lgintblo, na.rm = T),
>             control_funds = mean(v2lgfunds_ord, na.rm = T)) %>%
>   t()
> 
> sink("TableA1.tex")
> print(xtable(ta1))
> sink()
> 
> # table A2 ----------------------------------------------------------------
> 
> 
> ## Table A2
> m1 <- (lm(seatsharegov ~ v2x_regime + v2lgqstexp_ord  + country_name + factor(year), 
>           data = 
>             country_panel %>% filter(gov1seat > 0, execme != "-999", totalseats > 0, year >= 1975) %>% 
>             mutate(seatsharegov = gov1seat/totalseats,
>                    seatsharenongov = 1-seatsharegov) %>%
>             mutate(multiparty = as.numeric(v2elmulpar_ord >= 2))))
> 
> m2 <- (lm(seatsharegov ~ v2x_regime + v2lgqstexp_ord  +
>             v2lgintblo + v2lgfunds_ord + country_name + factor(year), 
>           data = 
>             country_panel %>% filter(gov1seat > 0, execme != "-999", totalseats > 0, year >= 1975) %>% 
>             mutate(seatsharegov = gov1seat/totalseats,
>                    seatsharenongov = 1-seatsharegov) %>%
>             mutate(multiparty = as.numeric(v2elmulpar_ord >= 2))))
> 
> m3 <- (lm(seatsharegov ~ v2x_regime + v2lgqstexp_ord  +
>             v2lgintblo + v2lgfunds_ord + log(e_population) + e_migdppcln + country_name + factor(year), 
>           data = 
>             country_panel %>% filter(gov1seat > 0, execme != "-999", totalseats > 0, year >= 1975) %>% 
>             mutate(seatsharegov = gov1seat/totalseats,
>                    seatsharenongov = 1-seatsharegov) %>%
>             mutate(multiparty = as.numeric(v2elmulpar_ord >= 2))))
> 
> sink("TableA2.tex")
> stargazer::stargazer(m1, m2, m3,
>                      dep.var.labels = c("Largest Party Seatshare"),
>                      star.cutoffs = c(0.05, 0.01, 0.001),
>                      covariate.labels = c("Electoral Autocracy", "Executive Queries",
>                                           "Bill Proposals", "Control of Funds",
>                                           "Log Pop.", "Log per cap GDP"),
>                      omit = c("Constant", "country*", "year*"),
>                      add.lines = list(c("Mean DV",  "0.72", "0.72", "0.72"),
>                                       c("Country FEs", rep("\\checkmark", 3)),
>                                       c("Year FEs", rep("\\checkmark",3))),
>                      omit.stat = c("f", "ser"))
> sink()
> 
> # table A4 ----------------------------------------------------------------
> 
> 
> # generate summary statistics
> # note table was formatted by hand
> ta4<- querydat %>% group_by(ministry) %>% 
>   summarise(n = n(), perc = 100*n/27186) %>%
>   filter(n> 300) %>%
>   arrange(tolower(ministry))
> 
> sink("TableA4.tex")
> print(xtable(ta4))
> sink()
> 
> ## table A5 ---------------------------------------------------------------------
> 
> sink("TableA5.tex")
> mpdat %>% 
>   dplyr::select(royalist, gov_full, leader, natlist, female, youth, former, actif, nwrit, log_nwrit) %>%
>   data.frame() %>%
>   stargazer(summary.stat = c("N", "mean", "sd", "min", "max"),
>             covariate.labels = c("Royalist", "Governing Coalition", "Committee Leader",
>                                  "National List", "Female", "Youth", "2007 Parliament",
>                                  "Civic Engagement", "Written Questions", "Log Written"))
> sink()
> 
> ## table A6 ---------------------------------------------------------------------
> 
> 
> sink("TableA6.tex")
> partycirc %>% 
>   ungroup() %>%
>   filter(group_code != "None" & group_code != "Alliance of the center") %>%
>   dplyr::select(voteshare2016, voteshare2011, n_wr_ln, nwrit, n_or_ln, 
>                 noral, npols, (population), internet, unemployment, illiteracy, 
>                 amazigh_low, urban) %>% as.data.frame() %>% 
>   stargazer(summary.stat = c("N", "mean", "sd", "min", "max"),
>             covariate.labels = c("Voteshare 2016", "Voteshare 2011",
>                                  "Log Written", "No. Written",
>                                  "Log Oral", "No. Oral",
>                                  "No. District Seats",
>                                  "Population", "Internet Access",
>                                  "Unemployment", "Illiteracy",
>                                  "Amazigh", "Urban"))
> sink()
> 
> 
> # table A7 ----------------------------------------------------------------
> 
> 
> writa <- glm.nb(nwrit ~ royalist, data = mpdat)
> 
> writb <- glm.nb(nwrit ~ royalist + leader + natlist +
>                   former + actif, data = mpdat)
> 
> writc <- glm.nb(nwrit ~ royalist + gov_full + leader + female + youth +
>                   former + actif, data = mpdat)
> 
> set.seed(123456)
> bs <- replicate(n = 1000, expr = block_bs_nb())
> se <- apply(bs, MARGIN = 1, FUN = sd, na.rm = T)
> 
> sea <- se[1:2]
> seb <- se[3:8]
> sec <- se[9:16]
> 
> 
> sink("TableA7.tex")
> stargazer(writa, writb, writc,
>           se = list(sea, seb, sec),
>           dep.var.labels = "Written Questions",
>           star.cutoffs = c(0.05, 0.01, 0.001),
>           omit = c("Constant"),
>           omit.stat = c("f", "ser"),
>           add.lines = list(c("Block Bootstrapped", rep(c("Yes"), 3))),
>           covariate.labels = c("Royalist", "Governing Coalition", "Committee Leader",
>                                "National List", "Female", "Youth",
>                                "2007 Parliament", "Civic Engagement"), no.space = T)
> sink()
> 
> # table A8 ----------------------------------------------------------------
> 
> win3_nonpart<- (lm(voteshare2016 ~ log_nonpart + n_or_ln + npols + voteshare2011 + region + log(population) +
>                      internet + unemployment + illiteracy + amazigh_low + urban, 
>                    data = partycirc))
> 
> win4_nonpart<- (lm(voteshare2016 ~ log_nonpart + n_or_ln + npols + voteshare2011 + factor(circid), 
>                    data = partycirc))
> 
> win5_nonpart<- (lm(votes2016 ~ log_nonpart + n_or_ln + npols + votes2011 +  region + log(population) +
>                      internet + unemployment + illiteracy + amazigh_low + urban, 
>                    data = partycirc))
> 
> win6_nonpart<- (lm(votes2016 ~ log_nonpart + n_or_ln + npols + votes2011 + factor(circid), 
>                    data = partycirc))
> 
> sink("TableA8.tex")
> stargazer(win3_nonpart, win4_nonpart, win5_nonpart, win6_nonpart,
>           dep.var.labels = c("Party Voteshare 2016", "Party Votes 2016"),
>           star.cutoffs = c(0.05, 0.01, 0.001),
>           omit = c("Constant", "reg", "circ*",
>                    "internet", "unem", "ama", "illit", "population", "urb"),
>           covariate.labels = c("Log Written - Partisan", "Log Oral",
>                                "No. District Seats Held", "2011 Voteshare",
>                                "2011 Votes"),
>           add.lines = list(c("Mean DV",  "0.19", "0.19", "12518", "12518"),
>                            c("Region FEs", "\\checkmark", "", "\\checkmark", ""),
>                            c("Dem. Controls", "\\checkmark", "", "\\checkmark", ""),
>                            c("District FEs", "",  "\\checkmark", "", "\\checkmark")),
>           omit.stat = c("f", "ser"))
> sink()
> 
> # table A9 ----------------------------------------------------------------
> 
> 
> win3_noint<- (lm(voteshare2016 ~ log_noint + n_or_ln + npols + voteshare2011+ region + log(population) +
>                    internet + unemployment + illiteracy +amazigh_low+ urban, data = partycirc))
> 
> win4_noint<- (lm(voteshare2016 ~ log_noint + n_or_ln +npols +voteshare2011+  factor(circid) , data = partycirc))
> 
> win5_noint<- (lm(votes2016 ~ log_noint + n_or_ln + npols + votes2011 +  region + log(population) +
>                    internet + unemployment + illiteracy + amazigh_low + urban, data = partycirc))
> 
> win6_noint<- (lm(votes2016 ~ log_noint + n_or_ln + npols + votes2011 + factor(circid), data = partycirc))
> 
> sink("TableA9.tex")
> stargazer(win3_noint, win4_noint, win5_noint, win6_noint,
>           dep.var.labels = c("Party Voteshare 2016", "Party Votes 2016"),
>           star.cutoffs = c(0.05, 0.01, 0.001),
>           omit = c("Constant", "reg", "circ*",
>                    "internet", "unem", "ama", "illit", "population", "urb"),
>           covariate.labels = c("Log Written - Excl Interior", "Log Oral",
>                                "No. District Seats Held", "2011 Voteshare",
>                                "2011 Votes"),
>           add.lines = list(c("Mean DV",  "0.19", "0.19", "12518", "12518"),
>                            c("Region FEs", "\\checkmark", "", "\\checkmark", ""),
>                            c("Dem. Controls", "\\checkmark", "", "\\checkmark", ""),
>                            c("District FEs", "",  "\\checkmark", "", "\\checkmark")),
>           omit.stat = c("f", "ser"))
> sink()
> 
> 
> # table A10 ---------------------------------------------------------------
> 
> 
> gov1 <- (lm(voteshare2016 ~ n_wr_ln + n_or_ln + npols + government + voteshare2011 + region + log(population) +
>               internet + unemployment + illiteracy + amazigh_low + urban, data = partycirc))
> 
> gov2 <- (lm(voteshare2016 ~ n_wr_ln + n_or_ln + npols + government + voteshare2011 + factor(circid)  , data = partycirc))
> 
> gov3 <- (lm(votes2016 ~ n_wr_ln + n_or_ln + npols + government + votes2011 +  region + log(population) +
>               internet + unemployment + illiteracy + amazigh_low + urban, data = partycirc))
> 
> gov4 <- (lm(votes2016 ~ n_wr_ln + n_or_ln + npols + government + votes2011 + factor(circid), data = partycirc))
> 
> sink("TableA10.tex")
> stargazer(gov1, gov2, gov3, gov4,
>           dep.var.labels = c("Party Voteshare 2016", "Party Votes 2016"),
>           star.cutoffs = c(0.05, 0.01, 0.001),
>           omit = c("Constant", "reg", "circ*",
>                    "internet", "unem", "ama", "illit", "population", "urb"),
>           covariate.labels = c("Log Written", "Log Oral",
>                                "No. District Seats Held", "In Gov. Coalition",
>                                "2011 Voteshare",
>                                "2011 Votes"),
>           add.lines = list(c("Mean DV",  "0.19", "0.19", "12518", "12518"),
>                            c("Region FEs", "\\checkmark", "", "\\checkmark", ""),
>                            c("Dem. Controls", "\\checkmark", "", "\\checkmark", ""),
>                            c("District FEs", "",  "\\checkmark", "", "\\checkmark")),
>           omit.stat = c("f", "ser"))
> sink()
> 
> 
> 
> # table A11 ---------------------------------------------------------------
> 
> 
> govroy1 <- (lm(delta_voteshare ~ n_wr_ln + region + government + log(population) +
>                  internet + unemployment + illiteracy + amazigh_low + urban , 
>                data = filter(partycirc, royalist == 1)))
> 
> govroy2 <- (lm(delta_voteshare ~ n_wr_ln + region + government + log(population) +
>                  internet + unemployment + illiteracy + amazigh_low + urban , 
>                data = filter(partycirc, royalist == 0)))
> 
> govroy3 <- (lm(delta_voteshare ~ n_wr_ln * royalist + region + government +  log(population) +
>                  internet + unemployment + illiteracy + amazigh_low + urban, 
>                data =partycirc))
> 
> govroy4 <- (lm(delta_votes ~ n_wr_ln + region + government + log(population) +
>                  internet + unemployment + illiteracy + amazigh_low + urban , 
>                data = filter(partycirc, royalist == 1)))
> 
> govroy5 <- (lm(delta_votes ~ n_wr_ln + region + government +  log(population) +
>                  internet + unemployment + illiteracy + amazigh_low + urban , 
>                data = filter(partycirc, royalist == 0)))
> 
> govroy6 <- (lm(delta_votes ~ n_wr_ln * royalist + region + government +  log(population) +
>                  internet + unemployment + illiteracy + amazigh_low + urban , 
>                data = partycirc))
> 
> sink("TableA11.tex")
> stargazer(govroy1, govroy2, govroy3, govroy4, govroy5, govroy6,
>           covariate.labels = c("Log Written", "Royalist", "In Gov. Coalition", "Log Writ*Royalist"),
>           omit = c("Constant", "reg", "circ*", "internet", "unem", "ama", "illit", "pop*", "urb"),
>           star.cutoffs = c(0.05, 0.01, 0.001),
>           dep.var.labels = c("Change in Voteshare 2011-2016", "Change in Votes 2011-2016"),
>           no.space = T,
>           omit.stat = c("adj.rsq", "f", "ser"),
>           add.lines = list(c("Sample", "Royalist", "Opposition", "All", "Royalist", "Opposition", "All"),
>                            c("Region FEs", rep("\\checkmark", 6)),
>                            c("Dem. Controls", rep("\\checkmark", 6))))
> sink()
> 
> # table A12 ---------------------------------------------------------------
> 
> 
> ans1 <- (lm(voteshare2016 ~ n_ans_ln + n_or_ln +npols + voteshare2011 + region + log(population) +
>               internet + unemployment + illiteracy + amazigh_low + urban, data = partycirc))
> 
> ans2<- (lm(voteshare2016 ~ n_ans_ln + n_or_ln + npols + voteshare2011 + factor(circid), data = partycirc))
> 
> ans3<- (lm(votes2016 ~ n_ans_ln + n_or_ln + npols + votes2011 +  region + log(population) +
>              internet + unemployment + illiteracy + amazigh_low + urban, data = partycirc))
> 
> ans4<- (lm(votes2016 ~ n_ans_ln + n_or_ln + npols + votes2011 + factor(circid), data = partycirc))
> 
> sink("TableA12.tex")
> stargazer(ans1, ans2, ans3, ans4,
>           dep.var.labels = c("Party Voteshare 2016", "Party Votes 2016"),
>           star.cutoffs = c(0.05, 0.01, 0.001),
>           omit = c("Constant", "reg", "circ*",
>                    "internet", "unem", "ama", "illit", "population", "urb"),
>           covariate.labels = c("Log Written (Answered)", "Log Oral",
>                                "No. District Seats Held", "2011 Voteshare",
>                                "2011 Votes"),
>           add.lines = list(c("Mean DV",  "0.19", "0.19", "12518", "12518"),
>                            c("Region FEs", "\\checkmark", "", "\\checkmark", ""),
>                            c("Dem. Controls", "\\checkmark", "", "\\checkmark", ""),
>                            c("District FEs", "",  "\\checkmark", "", "\\checkmark")),
>           omit.stat = c("adj.rsq","f", "ser"))
> sink()
> 
> # table A13 ---------------------------------------------------------------
> 
> 
> win_nom <- (lm(win ~ log_nwrit  + log_oral + royalist + leader + former + natlist, 
>                data = mpdat %>%
>                  filter(anynom == 1)))
> 
> win_head <- (lm(win ~ log_nwrit + log_oral + royalist + leader +former + natlist, 
>                 data = mpdat %>%
>                   filter(headnom == 1)))
> 
> win_nom_roy <- (lm(win ~log_nwrit * royalist + log_oral + leader + former + natlist , 
>                    data = mpdat %>%
>                      filter(anynom == 1)))
> 
> win_head_roy <- (lm(win ~log_nwrit * royalist +log_oral  + leader +former + natlist, 
>                     data = mpdat %>%
>                       filter(headnom == 1)))
> 
> sink("TableA13.tex")
> stargazer(win_nom, win_nom_roy, win_head, win_head_roy,
>           covariate.labels = c("Log Written", "Log Oral", "Royalist", "Committee Leader", 
>                                "2007 Parliament", "National List",
>                                "Log Writ x Royalist"),
>           dep.var.labels = c("Re-election"),
>           column.labels = c("|Nominated","|Nominated", "|Head of List","|Head of List"),
>           star.cutoffs = c(0.05, 0.01, 0.001),
>           omit = c("Constant"),
>           add.lines = list(c("Mean Re-election Rate","0.55", "0.55","0.60","0.60")),
>           no.space = T,
>           title = "Electoral Success in the 2016 Elections",
>           omit.stat = c("adj.rsq", "f", "ser"))
> sink()
> 
> ## table 14 --------------------------------------------------------------------
> 
> local1 <- (lm(voteshare2016 ~ log_local + n_or_ln + npols + voteshare2011 + region + log(population) +
>               internet + unemployment + illiteracy + amazigh_low + urban, data = partycirc))
> 
> local2 <- (lm(voteshare2016 ~ log_local + n_or_ln + npols + voteshare2011 + factor(circid), data = partycirc))
> 
> 
> local3 <- (lm(votes2016 ~ log_local + n_or_ln + npols + votes2011 +  region + log(population) +
>               internet + unemployment + illiteracy + amazigh_low + urban, data = partycirc))
> 
> local4 <- (lm(votes2016 ~ log_local + n_or_ln + npols + votes2011 + factor(circid), data = partycirc))
> 
> sink("TableA14.tex")
> stargazer(local1, local2, local3, local4,
>           dep.var.labels = c("Party Voteshare 2016", "Party Votes 2016"),
>           star.cutoffs = c(0.05, 0.01, 0.001),
>           omit = c("Constant", "reg", "circ*",
>                    "internet", "unem", "ama", "illit", "population", "urb"),
>           covariate.labels = c("Log Written (Local Only)", "Log Oral",
>                                "No. District Seats Held", "2011 Voteshare",
>                                "2011 Votes"),
>           add.lines = list(c("Mean DV",  "0.19", "0.19", "12518", "12518"),
>                            c("Region FEs", "\\checkmark", "", "\\checkmark", ""),
>                            c("Dem. Controls", "\\checkmark", "", "\\checkmark", ""),
>                            c("District FEs", "",  "\\checkmark", "", "\\checkmark")),
>           omit.stat = c("f", "ser"))
> sink()
> 
> ## table 15 --------------------------------------------------------------------
> 
> 
> ## see 04_rep_external.R
> 
> 
> ####
> 
> log_close()
> 

filter: removed 535 rows (17%), 2,527 rows remaining

NOTE: Log Print Time:  2024-06-03 17:27:28.630487 
NOTE: Elapsed Time: 1.18187403678894 secs 

mutate: new variable 'seatsharegov' (double) with 450 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:28.63907 
NOTE: Elapsed Time: 0.00858306884765625 secs 

        new variable 'seatsharenongov' (double) with 450 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:28.646812 
NOTE: Elapsed Time: 0.00774192810058594 secs 

group_by: one grouping variable (year)

NOTE: Log Print Time:  2024-06-03 17:27:28.659317 
NOTE: Elapsed Time: 0.012505054473877 secs 

summarise: now 43 rows and 5 columns, ungrouped

NOTE: Log Print Time:  2024-06-03 17:27:28.686873 
NOTE: Elapsed Time: 0.0275559425354004 secs 

filter: removed 1,214 rows (40%), 1,848 rows remaining

NOTE: Log Print Time:  2024-06-03 17:27:29.022784 
NOTE: Elapsed Time: 0.33591103553772 secs 

mutate: new variable 'seatsharegov' (double) with 342 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:29.033623 
NOTE: Elapsed Time: 0.0108389854431152 secs 

        new variable 'seatsharenongov' (double) with 342 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:29.042004 
NOTE: Elapsed Time: 0.00838112831115723 secs 

group_by: 2 grouping variables (year, v2x_regime)

NOTE: Log Print Time:  2024-06-03 17:27:29.052394 
NOTE: Elapsed Time: 0.0103898048400879 secs 

summarise: now 86 rows and 6 columns, one group variable remaining (year)

NOTE: Log Print Time:  2024-06-03 17:27:29.086101 
NOTE: Elapsed Time: 0.0337071418762207 secs 

filter: removed 1,399 rows (46%), 1,663 rows remaining

NOTE: Log Print Time:  2024-06-03 17:27:29.493336 
NOTE: Elapsed Time: 0.407234907150269 secs 

mutate: new variable 'seatsharegov' (double) with 293 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:29.502169 
NOTE: Elapsed Time: 0.00883293151855469 secs 

        new variable 'seatsharenongov' (double) with 293 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:29.50969 
NOTE: Elapsed Time: 0.00752115249633789 secs 

group_by: 2 grouping variables (year, e_region_world_2)

NOTE: Log Print Time:  2024-06-03 17:27:29.519759 
NOTE: Elapsed Time: 0.0100688934326172 secs 

summarise: now 215 rows and 6 columns, one group variable remaining (year)

NOTE: Log Print Time:  2024-06-03 17:27:29.56715 
NOTE: Elapsed Time: 0.0473911762237549 secs 

filter (grouped): removed 20 rows (9%), 195 rows remaining (removed 0 groups, 43 groups remaining)

NOTE: Log Print Time:  2024-06-03 17:27:29.577228 
NOTE: Elapsed Time: 0.010077953338623 secs 

filter: removed 368 rows (50%), 368 rows remaining

NOTE: Log Print Time:  2024-06-03 17:27:29.811399 
NOTE: Elapsed Time: 0.234170913696289 secs 

group_by: one grouping variable (circid)

NOTE: Log Print Time:  2024-06-03 17:27:29.818382 
NOTE: Elapsed Time: 0.00698304176330566 secs 

summarise: now 92 rows and 4 columns, ungrouped

NOTE: Log Print Time:  2024-06-03 17:27:29.825564 
NOTE: Elapsed Time: 0.00718188285827637 secs 

[1] "Warning: `summarise_each()` was deprecated in dplyr 0.7.0."
[2] "Warning: Please use `across()` instead."                   

NOTE: Log Print Time:  2024-06-03 17:27:30.299678 
NOTE: Elapsed Time: 0.474114179611206 secs 

mutate: new variable 'Nation' (double) with 2 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:30.312986 
NOTE: Elapsed Time: 0.0133078098297119 secs 

        new variable 'Region' (double) with 2 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:30.320614 
NOTE: Elapsed Time: 0.00762820243835449 secs 

        new variable 'Commune' (double) with 2 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:30.339048 
NOTE: Elapsed Time: 0.0184338092803955 secs 

        new variable 'Georeference' (double) with 2 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:30.345683 
NOTE: Elapsed Time: 0.00663518905639648 secs 

        new variable 'Casework' (double) with 2 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:30.357265 
NOTE: Elapsed Time: 0.0115818977355957 secs 

        new variable 'Complaint' (double) with 2 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:30.366532 
NOTE: Elapsed Time: 0.00926709175109863 secs 

        new variable 'Province' (double) with 2 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:30.375551 
NOTE: Elapsed Time: 0.00901889801025391 secs 

        new variable 'Royalist' (double) with 2 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:30.384995 
NOTE: Elapsed Time: 0.00944399833679199 secs 

group_by: one grouping variable (Royalist)

NOTE: Log Print Time:  2024-06-03 17:27:30.397448 
NOTE: Elapsed Time: 0.0124530792236328 secs 

[1] "Warning: `funs()` was deprecated in dplyr 0.8.0."                                                                                                                                                                                                                                
[2] "Warning: Please use a list of either functions or lambdas: \n\n  # Simple named list: \n  list(mean = mean, median = median)\n\n  # Auto named with `tibble::lst()`: \n  tibble::lst(mean, median)\n\n  # Using lambdas\n  list(~ mean(., trim = .2), ~ median(., na.rm = TRUE))"

NOTE: Log Print Time:  2024-06-03 17:27:30.469373 
NOTE: Elapsed Time: 0.0719249248504639 secs 

gather: reorganized (Nation, Region, Commune, Georeference, Casework, …) into (attribute, mn) [was 2x8, now 14x3]

NOTE: Log Print Time:  2024-06-03 17:27:30.486913 
NOTE: Elapsed Time: 0.0175399780273438 secs 

mutate: converted 'Royalist' from double to character (0 new NA)

NOTE: Log Print Time:  2024-06-03 17:27:30.497212 
NOTE: Elapsed Time: 0.0102989673614502 secs 

        converted 'attribute' from character to factor (0 new NA)

NOTE: Log Print Time:  2024-06-03 17:27:30.503601 
NOTE: Elapsed Time: 0.00638914108276367 secs 

        new variable 'rounded' (double) with 11 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:30.510128 
NOTE: Elapsed Time: 0.00652694702148438 secs 

filter: removed 27,292 rows (99%), 263 rows remaining

NOTE: Log Print Time:  2024-06-03 17:27:31.079128 
NOTE: Elapsed Time: 0.569000005722046 secs 

group_by: one grouping variable (year)

NOTE: Log Print Time:  2024-06-03 17:27:31.108085 
NOTE: Elapsed Time: 0.0289568901062012 secs 

summarise: now 3 rows and 4 columns, ungrouped

NOTE: Log Print Time:  2024-06-03 17:27:31.149922 
NOTE: Elapsed Time: 0.0418369770050049 secs 

filter: removed 535 rows (17%), 2,527 rows remaining

NOTE: Log Print Time:  2024-06-03 17:27:31.202606 
NOTE: Elapsed Time: 0.0526840686798096 secs 

mutate: new variable 'seatsharegov' (double) with 450 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:31.213823 
NOTE: Elapsed Time: 0.0112171173095703 secs 

        new variable 'seatsharenongov' (double) with 450 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:31.220846 
NOTE: Elapsed Time: 0.00702285766601562 secs 

mutate: new variable 'multiparty' (double) with 3 unique values and 72% NA

NOTE: Log Print Time:  2024-06-03 17:27:31.228707 
NOTE: Elapsed Time: 0.00786113739013672 secs 

filter: removed 535 rows (17%), 2,527 rows remaining

NOTE: Log Print Time:  2024-06-03 17:27:31.373306 
NOTE: Elapsed Time: 0.144598960876465 secs 

mutate: new variable 'seatsharegov' (double) with 450 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:31.384357 
NOTE: Elapsed Time: 0.0110509395599365 secs 

        new variable 'seatsharenongov' (double) with 450 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:31.394089 
NOTE: Elapsed Time: 0.00973200798034668 secs 

mutate: new variable 'multiparty' (double) with 3 unique values and 72% NA

NOTE: Log Print Time:  2024-06-03 17:27:31.405906 
NOTE: Elapsed Time: 0.0118169784545898 secs 

filter: removed 535 rows (17%), 2,527 rows remaining

NOTE: Log Print Time:  2024-06-03 17:27:31.70347 
NOTE: Elapsed Time: 0.297564029693604 secs 

mutate: new variable 'seatsharegov' (double) with 450 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:31.71958 
NOTE: Elapsed Time: 0.0161099433898926 secs 

        new variable 'seatsharenongov' (double) with 450 unique values and 0% NA

NOTE: Log Print Time:  2024-06-03 17:27:31.735353 
NOTE: Elapsed Time: 0.0157730579376221 secs 

mutate: new variable 'multiparty' (double) with 3 unique values and 72% NA

NOTE: Log Print Time:  2024-06-03 17:27:31.751008 
NOTE: Elapsed Time: 0.0156550407409668 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:27:31.970292 
NOTE: Elapsed Time: 0.219284057617188 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:27:31.977699 
NOTE: Elapsed Time: 0.00740694999694824 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:27:31.987635 
NOTE: Elapsed Time: 0.00993585586547852 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:27:31.994652 
NOTE: Elapsed Time: 0.00701713562011719 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:27:32.001657 
NOTE: Elapsed Time: 0.00700497627258301 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:27:32.02359 
NOTE: Elapsed Time: 0.0219330787658691 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:27:32.16382 
NOTE: Elapsed Time: 0.140229940414429 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:27:32.330202 
NOTE: Elapsed Time: 0.166382074356079 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:27:32.336499 
NOTE: Elapsed Time: 0.00629687309265137 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:27:32.348065 
NOTE: Elapsed Time: 0.0115659236907959 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:27:32.355578 
NOTE: Elapsed Time: 0.00751304626464844 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:27:32.361377 
NOTE: Elapsed Time: 0.0057990550994873 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:27:32.393939 
NOTE: Elapsed Time: 0.0325620174407959 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:27:32.532713 
NOTE: Elapsed Time: 0.138773918151855 secs 

group_by: one grouping variable (ministry)

NOTE: Log Print Time:  2024-06-03 17:27:32.724026 
NOTE: Elapsed Time: 0.191313028335571 secs 

summarise: now 31 rows and 3 columns, ungrouped

NOTE: Log Print Time:  2024-06-03 17:27:32.73297 
NOTE: Elapsed Time: 0.00894403457641602 secs 

filter: removed 11 rows (35%), 20 rows remaining

NOTE: Log Print Time:  2024-06-03 17:27:32.740454 
NOTE: Elapsed Time: 0.00748395919799805 secs 

ungroup: no grouping variables remain

NOTE: Log Print Time:  2024-06-03 17:27:33.043795 
NOTE: Elapsed Time: 0.303341150283813 secs 

filter: removed 470 rows (64%), 266 rows remaining

NOTE: Log Print Time:  2024-06-03 17:27:33.055621 
NOTE: Elapsed Time: 0.0118257999420166 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:35.015931 
NOTE: Elapsed Time: 1.9603099822998 secs 

Warning: alternation limit reached 

NOTE: Log Print Time:  2024-06-03 17:27:36.441629 
NOTE: Elapsed Time: 1.42569804191589 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:37.63879 
NOTE: Elapsed Time: 1.19716095924377 secs 

Warning: alternation limit reached 

NOTE: Log Print Time:  2024-06-03 17:27:37.677266 
NOTE: Elapsed Time: 0.0384759902954102 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:40.589399 
NOTE: Elapsed Time: 2.91213321685791 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:40.606325 
NOTE: Elapsed Time: 0.0169258117675781 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:40.618928 
NOTE: Elapsed Time: 0.0126030445098877 secs 

Warning: alternation limit reached 

NOTE: Log Print Time:  2024-06-03 17:27:40.658377 
NOTE: Elapsed Time: 0.0394489765167236 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:41.087092 
NOTE: Elapsed Time: 0.428714990615845 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:42.097726 
NOTE: Elapsed Time: 1.01063418388367 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:43.970883 
NOTE: Elapsed Time: 1.87315678596497 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:44.238333 
NOTE: Elapsed Time: 0.267450094223022 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:44.249446 
NOTE: Elapsed Time: 0.0111129283905029 secs 

Warning: alternation limit reached 

NOTE: Log Print Time:  2024-06-03 17:27:44.283236 
NOTE: Elapsed Time: 0.033790111541748 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:44.864077 
NOTE: Elapsed Time: 0.580841064453125 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:46.343259 
NOTE: Elapsed Time: 1.47918200492859 secs 

Warning: alternation limit reached 

NOTE: Log Print Time:  2024-06-03 17:27:46.365122 
NOTE: Elapsed Time: 0.0218629837036133 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:49.247196 
NOTE: Elapsed Time: 2.88207387924194 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:49.263685 
NOTE: Elapsed Time: 0.0164890289306641 secs 

Warning: alternation limit reached 

NOTE: Log Print Time:  2024-06-03 17:27:49.304753 
NOTE: Elapsed Time: 0.0410680770874023 secs 

Warning: alternation limit reached 

NOTE: Log Print Time:  2024-06-03 17:27:51.294326 
NOTE: Elapsed Time: 1.98957300186157 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:51.607406 
NOTE: Elapsed Time: 0.313079833984375 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:51.718507 
NOTE: Elapsed Time: 0.111101150512695 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:52.721506 
NOTE: Elapsed Time: 1.00299906730652 secs 

Warning: alternation limit reached 

NOTE: Log Print Time:  2024-06-03 17:27:52.764998 
NOTE: Elapsed Time: 0.0434918403625488 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:53.896385 
NOTE: Elapsed Time: 1.13138699531555 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:53.909671 
NOTE: Elapsed Time: 0.0132861137390137 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:53.929313 
NOTE: Elapsed Time: 0.0196418762207031 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:53.949299 
NOTE: Elapsed Time: 0.0199861526489258 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:53.967983 
NOTE: Elapsed Time: 0.018683910369873 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.000499 
NOTE: Elapsed Time: 0.0325160026550293 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.029739 
NOTE: Elapsed Time: 0.0292398929595947 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.036283 
NOTE: Elapsed Time: 0.00654411315917969 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.06178 
NOTE: Elapsed Time: 0.0254969596862793 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.068287 
NOTE: Elapsed Time: 0.00650691986083984 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.077825 
NOTE: Elapsed Time: 0.00953817367553711 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.08912 
NOTE: Elapsed Time: 0.0112948417663574 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.103225 
NOTE: Elapsed Time: 0.0141050815582275 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.114825 
NOTE: Elapsed Time: 0.0116000175476074 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.123364 
NOTE: Elapsed Time: 0.00853896141052246 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.143081 
NOTE: Elapsed Time: 0.0197169780731201 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.172957 
NOTE: Elapsed Time: 0.0298759937286377 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.18324 
NOTE: Elapsed Time: 0.0102829933166504 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.18968 
NOTE: Elapsed Time: 0.00644016265869141 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.218721 
NOTE: Elapsed Time: 0.0290408134460449 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.231557 
NOTE: Elapsed Time: 0.0128359794616699 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.243529 
NOTE: Elapsed Time: 0.011972188949585 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.258278 
NOTE: Elapsed Time: 0.0147488117218018 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.26857 
NOTE: Elapsed Time: 0.0102920532226562 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.280868 
NOTE: Elapsed Time: 0.0122981071472168 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:54.292562 
NOTE: Elapsed Time: 0.0116939544677734 secs 

Warning: alternation limit reached 

NOTE: Log Print Time:  2024-06-03 17:27:54.302722 
NOTE: Elapsed Time: 0.010159969329834 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:55.086161 
NOTE: Elapsed Time: 0.783438920974731 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.025438 
NOTE: Elapsed Time: 0.939277172088623 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.043519 
NOTE: Elapsed Time: 0.0180809497833252 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.065441 
NOTE: Elapsed Time: 0.0219218730926514 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.083561 
NOTE: Elapsed Time: 0.0181200504302979 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.102178 
NOTE: Elapsed Time: 0.0186171531677246 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.120288 
NOTE: Elapsed Time: 0.0181097984313965 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.137434 
NOTE: Elapsed Time: 0.017146110534668 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.14808 
NOTE: Elapsed Time: 0.0106461048126221 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.154017 
NOTE: Elapsed Time: 0.00593686103820801 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.184558 
NOTE: Elapsed Time: 0.030540943145752 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.196987 
NOTE: Elapsed Time: 0.0124289989471436 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.210423 
NOTE: Elapsed Time: 0.0134360790252686 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.22757 
NOTE: Elapsed Time: 0.0171470642089844 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.244507 
NOTE: Elapsed Time: 0.0169370174407959 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.251727 
NOTE: Elapsed Time: 0.00722002983093262 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.2618 
NOTE: Elapsed Time: 0.0100729465484619 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.29277 
NOTE: Elapsed Time: 0.0309698581695557 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.306636 
NOTE: Elapsed Time: 0.0138661861419678 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.319516 
NOTE: Elapsed Time: 0.0128798484802246 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.331837 
NOTE: Elapsed Time: 0.0123209953308105 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.344997 
NOTE: Elapsed Time: 0.0131599903106689 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.352031 
NOTE: Elapsed Time: 0.0070340633392334 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.370594 
NOTE: Elapsed Time: 0.0185630321502686 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.380065 
NOTE: Elapsed Time: 0.00947093963623047 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:27:56.390462 
NOTE: Elapsed Time: 0.0103969573974609 secs 

Warning: alternation limit reached 

NOTE: Log Print Time:  2024-06-03 17:27:56.399622 
NOTE: Elapsed Time: 0.00916004180908203 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:00.774759 
NOTE: Elapsed Time: 4.37513709068298 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:01.1532 
NOTE: Elapsed Time: 0.378440856933594 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:01.227122 
NOTE: Elapsed Time: 0.0739221572875977 secs 

Warning: alternation limit reached 

NOTE: Log Print Time:  2024-06-03 17:28:04.325786 
NOTE: Elapsed Time: 3.09866404533386 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:04.757882 
NOTE: Elapsed Time: 0.432096004486084 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:04.773222 
NOTE: Elapsed Time: 0.0153398513793945 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:04.793552 
NOTE: Elapsed Time: 0.0203299522399902 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:04.811827 
NOTE: Elapsed Time: 0.0182750225067139 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:04.827402 
NOTE: Elapsed Time: 0.0155751705169678 secs 

Warning: alternation limit reached 

NOTE: Log Print Time:  2024-06-03 17:28:04.85856 
NOTE: Elapsed Time: 0.0311579704284668 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.385636 
NOTE: Elapsed Time: 0.527076005935669 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.401541 
NOTE: Elapsed Time: 0.0159049034118652 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.426145 
NOTE: Elapsed Time: 0.0246040821075439 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.443385 
NOTE: Elapsed Time: 0.0172398090362549 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.463038 
NOTE: Elapsed Time: 0.0196530818939209 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.472913 
NOTE: Elapsed Time: 0.00987505912780762 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.480132 
NOTE: Elapsed Time: 0.00721907615661621 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.486599 
NOTE: Elapsed Time: 0.00646686553955078 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.496392 
NOTE: Elapsed Time: 0.00979304313659668 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.508383 
NOTE: Elapsed Time: 0.011991024017334 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.51875 
NOTE: Elapsed Time: 0.0103669166564941 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.526567 
NOTE: Elapsed Time: 0.00781702995300293 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.5376 
NOTE: Elapsed Time: 0.0110330581665039 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.545632 
NOTE: Elapsed Time: 0.00803184509277344 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.55409 
NOTE: Elapsed Time: 0.00845813751220703 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.564188 
NOTE: Elapsed Time: 0.0100979804992676 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.578644 
NOTE: Elapsed Time: 0.014456033706665 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.589116 
NOTE: Elapsed Time: 0.0104720592498779 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.619115 
NOTE: Elapsed Time: 0.0299990177154541 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.630279 
NOTE: Elapsed Time: 0.0111639499664307 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.641708 
NOTE: Elapsed Time: 0.0114288330078125 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.650345 
NOTE: Elapsed Time: 0.0086371898651123 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.668885 
NOTE: Elapsed Time: 0.0185399055480957 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.677178 
NOTE: Elapsed Time: 0.00829291343688965 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.687993 
NOTE: Elapsed Time: 0.0108151435852051 secs 

Warning: alternation limit reached 

NOTE: Log Print Time:  2024-06-03 17:28:05.694948 
NOTE: Elapsed Time: 0.00695490837097168 secs 

Warning: glm.fit: algorithm did not converge 

NOTE: Log Print Time:  2024-06-03 17:28:05.825781 
NOTE: Elapsed Time: 0.130833148956299 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:06.343875 
NOTE: Elapsed Time: 0.518093824386597 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:06.349064 
NOTE: Elapsed Time: 0.00518918037414551 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:06.359509 
NOTE: Elapsed Time: 0.0104448795318604 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:06.366854 
NOTE: Elapsed Time: 0.00734496116638184 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:06.38487 
NOTE: Elapsed Time: 0.0180160999298096 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:06.413825 
NOTE: Elapsed Time: 0.0289549827575684 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:06.458263 
NOTE: Elapsed Time: 0.0444378852844238 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:06.464149 
NOTE: Elapsed Time: 0.00588607788085938 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:06.473266 
NOTE: Elapsed Time: 0.00911688804626465 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:06.480153 
NOTE: Elapsed Time: 0.00688719749450684 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:06.508592 
NOTE: Elapsed Time: 0.0284388065338135 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:06.56716 
NOTE: Elapsed Time: 0.058568000793457 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:06.844894 
NOTE: Elapsed Time: 0.277734041213989 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:06.852029 
NOTE: Elapsed Time: 0.00713515281677246 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:06.862218 
NOTE: Elapsed Time: 0.0101888179779053 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:06.875773 
NOTE: Elapsed Time: 0.0135550498962402 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:06.889974 
NOTE: Elapsed Time: 0.0142011642456055 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:06.924443 
NOTE: Elapsed Time: 0.0344688892364502 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:07.05206 
NOTE: Elapsed Time: 0.127616882324219 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.154659 
NOTE: Elapsed Time: 0.102599143981934 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.160168 
NOTE: Elapsed Time: 0.0055088996887207 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.1689 
NOTE: Elapsed Time: 0.00873208045959473 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.198346 
NOTE: Elapsed Time: 0.0294458866119385 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.206345 
NOTE: Elapsed Time: 0.00799918174743652 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:07.223253 
NOTE: Elapsed Time: 0.0169079303741455 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:07.291765 
NOTE: Elapsed Time: 0.068511962890625 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.600262 
NOTE: Elapsed Time: 0.308496952056885 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.607943 
NOTE: Elapsed Time: 0.00768113136291504 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.619322 
NOTE: Elapsed Time: 0.0113790035247803 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.642934 
NOTE: Elapsed Time: 0.0236120223999023 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.650788 
NOTE: Elapsed Time: 0.00785398483276367 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:07.671684 
NOTE: Elapsed Time: 0.0208959579467773 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:07.788228 
NOTE: Elapsed Time: 0.116544008255005 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.954589 
NOTE: Elapsed Time: 0.166360855102539 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.960121 
NOTE: Elapsed Time: 0.00553202629089355 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.969745 
NOTE: Elapsed Time: 0.00962400436401367 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.977002 
NOTE: Elapsed Time: 0.00725698471069336 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:07.98432 
NOTE: Elapsed Time: 0.00731801986694336 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:08.029566 
NOTE: Elapsed Time: 0.0452461242675781 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:08.095776 
NOTE: Elapsed Time: 0.0662100315093994 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:08.351563 
NOTE: Elapsed Time: 0.255786895751953 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:08.356521 
NOTE: Elapsed Time: 0.00495791435241699 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:08.363935 
NOTE: Elapsed Time: 0.00741410255432129 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:08.371979 
NOTE: Elapsed Time: 0.00804400444030762 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:08.375858 
NOTE: Elapsed Time: 0.00387907028198242 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:08.39441 
NOTE: Elapsed Time: 0.0185518264770508 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:08.461947 
NOTE: Elapsed Time: 0.0675370693206787 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:08.641267 
NOTE: Elapsed Time: 0.179320096969604 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:08.652026 
NOTE: Elapsed Time: 0.0107588768005371 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:08.686406 
NOTE: Elapsed Time: 0.0343799591064453 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:08.760083 
NOTE: Elapsed Time: 0.0736770629882812 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:08.773235 
NOTE: Elapsed Time: 0.0131521224975586 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:08.786976 
NOTE: Elapsed Time: 0.0137410163879395 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:08.875727 
NOTE: Elapsed Time: 0.0887508392333984 secs 

filter: removed 368 rows (50%), 368 rows remaining

NOTE: Log Print Time:  2024-06-03 17:28:09.014714 
NOTE: Elapsed Time: 0.138987064361572 secs 

filter: removed 368 rows (50%), 368 rows remaining

NOTE: Log Print Time:  2024-06-03 17:28:09.053476 
NOTE: Elapsed Time: 0.038762092590332 secs 

filter: removed 368 rows (50%), 368 rows remaining

NOTE: Log Print Time:  2024-06-03 17:28:09.104866 
NOTE: Elapsed Time: 0.0513899326324463 secs 

filter: removed 368 rows (50%), 368 rows remaining

NOTE: Log Print Time:  2024-06-03 17:28:09.177118 
NOTE: Elapsed Time: 0.0722520351409912 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:09.242857 
NOTE: Elapsed Time: 0.0657389163970947 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:09.250643 
NOTE: Elapsed Time: 0.00778603553771973 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:09.25883 
NOTE: Elapsed Time: 0.00818705558776855 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:09.266241 
NOTE: Elapsed Time: 0.00741100311279297 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:09.275131 
NOTE: Elapsed Time: 0.00888991355895996 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:09.303854 
NOTE: Elapsed Time: 0.0287230014801025 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:09.324246 
NOTE: Elapsed Time: 0.0203919410705566 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:09.373738 
NOTE: Elapsed Time: 0.0494921207427979 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:09.417966 
NOTE: Elapsed Time: 0.0442278385162354 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:09.598226 
NOTE: Elapsed Time: 0.180260181427002 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:09.603875 
NOTE: Elapsed Time: 0.00564885139465332 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:09.613271 
NOTE: Elapsed Time: 0.00939607620239258 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:09.625951 
NOTE: Elapsed Time: 0.0126800537109375 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:09.631139 
NOTE: Elapsed Time: 0.00518798828125 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:09.642862 
NOTE: Elapsed Time: 0.0117230415344238 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:09.676552 
NOTE: Elapsed Time: 0.0336899757385254 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:09.707311 
NOTE: Elapsed Time: 0.0307588577270508 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:09.744034 
NOTE: Elapsed Time: 0.0367231369018555 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:09.989707 
NOTE: Elapsed Time: 0.245672941207886 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:09.998397 
NOTE: Elapsed Time: 0.00869011878967285 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.011433 
NOTE: Elapsed Time: 0.013035774230957 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.020927 
NOTE: Elapsed Time: 0.00949406623840332 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.032636 
NOTE: Elapsed Time: 0.0117089748382568 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:10.074906 
NOTE: Elapsed Time: 0.0422701835632324 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:10.162935 
NOTE: Elapsed Time: 0.0880289077758789 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.278577 
NOTE: Elapsed Time: 0.115642070770264 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.284191 
NOTE: Elapsed Time: 0.00561380386352539 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.291692 
NOTE: Elapsed Time: 0.00750112533569336 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.309498 
NOTE: Elapsed Time: 0.0178060531616211 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.328583 
NOTE: Elapsed Time: 0.0190849304199219 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:10.346037 
NOTE: Elapsed Time: 0.0174539089202881 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:10.427902 
NOTE: Elapsed Time: 0.0818650722503662 secs 

filter: removed 241 rows (58%), 172 rows remaining

NOTE: Log Print Time:  2024-06-03 17:28:10.511041 
NOTE: Elapsed Time: 0.0831389427185059 secs 

filter: removed 277 rows (67%), 136 rows remaining

NOTE: Log Print Time:  2024-06-03 17:28:10.524099 
NOTE: Elapsed Time: 0.0130581855773926 secs 

filter: removed 241 rows (58%), 172 rows remaining

NOTE: Log Print Time:  2024-06-03 17:28:10.568108 
NOTE: Elapsed Time: 0.0440089702606201 secs 

filter: removed 277 rows (67%), 136 rows remaining

NOTE: Log Print Time:  2024-06-03 17:28:10.600657 
NOTE: Elapsed Time: 0.0325489044189453 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.689092 
NOTE: Elapsed Time: 0.0884349346160889 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.694542 
NOTE: Elapsed Time: 0.00545001029968262 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.704308 
NOTE: Elapsed Time: 0.0097661018371582 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.712202 
NOTE: Elapsed Time: 0.00789403915405273 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.719685 
NOTE: Elapsed Time: 0.00748300552368164 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:10.729019 
NOTE: Elapsed Time: 0.00933384895324707 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:10.76201 
NOTE: Elapsed Time: 0.0329911708831787 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.810716 
NOTE: Elapsed Time: 0.0487058162689209 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.817547 
NOTE: Elapsed Time: 0.00683116912841797 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.825807 
NOTE: Elapsed Time: 0.00826001167297363 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.834185 
NOTE: Elapsed Time: 0.0083777904510498 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:10.863669 
NOTE: Elapsed Time: 0.0294840335845947 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:10.878909 
NOTE: Elapsed Time: 0.0152401924133301 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:10.925094 
NOTE: Elapsed Time: 0.046184778213501 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:11.201273 
NOTE: Elapsed Time: 0.276179075241089 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:11.207804 
NOTE: Elapsed Time: 0.0065310001373291 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:11.215608 
NOTE: Elapsed Time: 0.00780391693115234 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:11.22343 
NOTE: Elapsed Time: 0.00782203674316406 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:11.228044 
NOTE: Elapsed Time: 0.00461411476135254 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:11.25571 
NOTE: Elapsed Time: 0.0276658535003662 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:11.345926 
NOTE: Elapsed Time: 0.0902161598205566 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:11.45313 
NOTE: Elapsed Time: 0.107203960418701 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:11.457429 
NOTE: Elapsed Time: 0.00429892539978027 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:11.465273 
NOTE: Elapsed Time: 0.00784397125244141 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:11.473232 
NOTE: Elapsed Time: 0.00795912742614746 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:28:11.481224 
NOTE: Elapsed Time: 0.00799202919006348 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:11.493816 
NOTE: Elapsed Time: 0.0125918388366699 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:28:11.559609 
NOTE: Elapsed Time: 0.0657930374145508 secs 

========================================================================= 
Log End Time: 2024-06-03 17:28:11.673755 
Log Elapsed Time: 0 00:00:44 
========================================================================= 
